docs: def from_ashrae_revised_clear_sky(cls, location, monthly_tau_beam,
                                        monthly_tau_diffuse, timestep=1,
                                        is_leap_year=False):
          """Create a wea object representing an ASHRAE Revised Clear Sky ("Tau Model")
  
          ASHRAE Revised Clear Skies are intended to determine peak solar load
          and sizing parmeters for HVAC systems.  The revised clear sky is
          currently the default recommended sky model used to autosize HVAC
          systems in EnergyPlus. For more information on the ASHRAE Revised Clear
          Sky model, see the EnergyPlus Engineering Reference:
          https://bigladdersoftware.com/epx/docs/8-9/engineering-reference/climate-calculations.html
  
          Args:
              location: Ladybug location object.
              monthly_tau_beam: A list of 12 float values indicating the beam
                  optical depth of the sky at each month of the year.
              monthly_tau_diffuse: A list of 12 float values indicating the
                  diffuse optical depth of the sky at each month of the year.
              timestep: An optional integer to set the number of time steps per
                  hour. Default is 1 for one value per hour.
              is_leap_year: A boolean to indicate if values are representing a leap year.
                  Default is False.
          """
          # extract metadata
          metadata = {'source': location.source, 'country': location.country,
                      'city': location.city}
  
          # create sunpath and get altitude at every timestep of the year
          sp = Sunpath.from_location(location)
          sp.is_leap_year = is_leap_year
          altitudes = [[] for i in range(12)]
          dates = cls._get_datetimes(timestep, is_leap_year)
          for t_date in dates:
              sun = sp.calculate_sun_from_date_time(t_date)
              altitudes[sun.datetime.month - 1].append(sun.altitude)
  
          # run all of the months through the ashrae_revised_clear_sky model
          direct_norm, diffuse_horiz = [], []
          for i_mon, alt_list in enumerate(altitudes):
              dir_norm_rad, dif_horiz_rad = ashrae_revised_clear_sky(
                  alt_list, monthly_tau_beam[i_mon], monthly_tau_diffuse[i_mon])
              direct_norm.extend(dir_norm_rad)
              diffuse_horiz.extend(dif_horiz_rad)
  
          direct_norm_rad, diffuse_horiz_rad = \
              cls._get_data_collections(direct_norm, diffuse_horiz,
                                        metadata, timestep, is_leap_year)
  
          return cls(location, direct_norm_rad, diffuse_horiz_rad, timestep, is_leap_year)